Instructions to use theoberva/UBCO-Model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theoberva/UBCO-Model-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="theoberva/UBCO-Model-v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("theoberva/UBCO-Model-v2") model = AutoModelForImageClassification.from_pretrained("theoberva/UBCO-Model-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 92
bc52e14 -
Training in progress, epoch 82
e0d386b -
Training in progress, epoch 72
246796c -
Training in progress, epoch 62
1c6a77d -
Training in progress, epoch 51
abd3e2e -
Training in progress, epoch 41
f6ff288 -
Training in progress, epoch 31
3bbc38b -
Training in progress, epoch 21
88f9c9a -
Training in progress, epoch 11
1da7779 -
Training in progress, epoch 1
848d786
-
Upload processor
19deb95 -
Upload Swinv2ForImageClassification
202d07f -
Upload Swinv2ForImageClassification
21eec15 -
initial commit
b6a5ebd